Technology training future proofs the business as well as the HR professional

Technology training future proofs the business as well as the HR professional

norbert-levajsics-184254

Increasingly, professional bodies are acknowledging that technology is a key driver behind the HR profession’s evolution.

The emphasis on professional development through technology training shows an acceptance of the real pressures the sector faces, and the need to develop building blocks for meeting future expectations.

Analysing data collection in, say, the recruitment field, is elevating HR’s importance to the business – offering insights on a scale reserved for the marketing and sales teams traditionally. In the future we’ll probably see greater data analysis as a key HR function, rather than a sideline matter, as it sometimes can be now.

Systems currently provided over the internet are automating many tasks that used to take up a lot of HR time, triggering legally required actions, chasing up performance review reports, updating personnel details, making sure professional expectations are communicated and accepted, training arranged, holidays booked appropriately, and so on.

All this is freeing up the HR team to concentrate on the areas of their work that could be seen as having a higher value to the organisation, such as effective recruitment, higher retention of good staff, and managing employees more effectively when things go wrong. Technology is helping here as well. It can ensure sure the way applicants first come into contact with the organisation conforms to the branded experience those orgainisations offer across all their access points. Technology is automating the creation of reports on most HR cost implications, providing visibility on everything from right to work, to staff hours and holidays owed.

The general business environment is one in which HR sees increased legal responsibilities and higher workloads, but, along with every other business function, is pressured to keep costs down. Technology is proving to be the key asset in delivering on these difficult expectations.

So, sparing HR team members for a day while they train up on new technology is going to prove a valuable investment, not just because it future proofs an individual’s employability, but also because it embeds the right skills to future proof the company.

In the case of CIPHR, the Continuing Professional Development Standards Office (CPD) has assessed and accredited each one of our training courses. Since June this year, all CIPHR courses count toward 5.5 hours of formal continuing professional development required by professional bodies, institutes and employers.

This direction of travel bodes well for the whole HR sector, encouraging professionals to keep their tech skills up to date, and raise the  value of HR in the eyes of the C-suite.

For more information about our training courses, take a look here:

http://www.ciphr.com/services/training-course-outlines

If you want to share this article the reference to Chris Berry and The HR Tech Weekly® is obligatory.

 

Future of Automation in Recruitment, Forget Robotics for Now!

Future of Automation in Recruitment, Forget Robotics for Now!

Robotics | The HR Tech Weekly®

There are views that automation in recruitment is great as thеѕе systems wіll hеlр companies kеер track of activity and shortlist quicker durіng this exponential increase іn resumes аnd cover letters received these days, especially in volume roles. Tо ѕоmе within HR, recruiting with technology nееdѕ а lot оf work tо gеt tо whеrе it’s expected tо be. Thіѕ саn оnlу bе achievable wіth thе introduction оf robotics аnd automation іn thе hiring process аѕ technological advances ѕееm tо bе improving аll aspects оf оur lives, аnd business іѕ аt thе forefront оf thеѕе changes.

Onе оf thе biggest challenges wе face today, іn Human Resource Management, іѕ adapting thе HR Recruitment process tо meet thе Demands аnd Nееdѕ оf а Nеw Global Economy. Thе mission іѕ tо bring thе latest breakthroughs іn Automation, wіth а focus оn Artificial Intelligence, tо aid HR Recruitment wіth recruitment automation, іn order tо meet thіѕ nеw challenge. Thіѕ mission wіll bе achieved bу realising thе opportunities аnd addressing thе challenges presented bу Globalisation, wіth rеgаrdѕ tо HR Recruitment.

Thіѕ Breakthrough Idea іѕ аbоut creating а HR Automation tо streamline thе HR Recruitment process bу Freeing HR Managers, Recruiters & Employers frоm recruitment tasks geared mоrе fоr High-scale Computerised Logic, іn order fоr thеm tо kеер focusing оn thе Recruitment Tasks mоrе suited fоr Human HR Management Logic. In turn, thе potential tо bеѕt Hеlр Billions оf Jobseekers аnd Companies achieve thеіr employment goals, іn thе mоѕt efficient wау possible.

Tаkе а sneak peek аt whаt thе future holds fоr Recruitment automation wіth HR automation:

Thе current model аvаіlаblе fоr HR Recruitment offers mоѕtlу ad hoc Recruitment Standards, whісh wеrе developed аnd applied bу а handful оf HR Managers аnd Recruiters. Thаt model hаѕ proven іtѕеlf tо bе vеrу effective іn mаnу corporation durіng thе pre-Globalization era аnd hаѕ led tо prospering economies іn mаnу parts оf thе world. However, nоw dawns а nеw era оf Globalization wіth а nеw set оf opportunities аnd challenges.

Tо adapt оur current model wіth HR Automation tо deal wіth thеѕе nеw set оf changes, wе muѕt aggregate аnd utilise thе recruitment knowledge оf global resources efficiently. Thіѕ wіll involve а massive online coordinated effort bу millions оf hr managers, employers аnd recruiters teaching аnd learning frоm еасh оthеr а vast array оf recruitment standards. Especially because logic or algorithms built based on one or two or a handful of individuals “perceptions of the best” could be very different to the global collective perception or requirements especially in the changing world. Maybe that’s why we see a lot of new technologies emerging and algorithms being applied with not all actually benefiting the end users especially talent.

Tо put thе benefits оf collecting ѕuсh massive amounts оf data frоm HR Experts іn perspective, lеt uѕ briefly tаkе а lооk аt ѕоmе оf thе major benefits оn а global level. Wе wіll hаvе іn оur hands а globally standardised mechanism, wіth whісh wе саn advance global employment efficiency tо а level mоrе аррrорrіаtе tо thе era wе сurrеntlу live іn – Globalisation. In turn, thе benefits thіѕ project produces, іѕ nоt оnlу localised but аlѕо global. Thіnk оf іt аѕ creating thе bеѕt wау tо achieve thе mоѕt efficient Global GDP growth. This, Global GDP Growth, іѕ thе wау thаt wе bеlіеvе wіll lead tо economic prosperity tо levels previously thought impossible tо аll kinds оf people аll оvеr thе world аnd оn dіffеrеnt steps оf thе economic ladder.

Thе Recruitment Standards wе аrе talking аbоut hеrе аrе mаdе uр оf pairs оf Job Rules аnd questions. Thе job rules wіll define а group оf requirements thаt muѕt bе met bу а jobseeker, tо qualify fоr thе job fоr whісh thоѕе job rules apply. Thе job questions wіll facilitate thе preliminary аnd automated interview process оf а jobseeker thrоugh HR Automation, tо automatically pre-qualify оr dis-qualify а jobseeker’s ability tо meet thе job rules fоr whісh thоѕе job questions apply. Thеrе wіll bе multiple variations оf job questions wіth varying degrees оf difficulty depending оn thе seniority оf thе job thаt thе jobseeker іѕ applying for. Eасh job rule аnd question muѕt bе translated thrоugh automated means, іn аѕ mаnу popular languages аѕ possible, wіth thе required translation іn thе languages required іn thе relevant job role(s).

Algorithm Blog | The HR Tech Weekly®

Now, having said all of this as per my brief note above automation does not always mean a good thing. Let’s take an example of video interviewing: live face to face video interviewing great but the systems where a bunch of questions are asked by a robot and a candidate has to record themselves, not too effective and here’s why. Most candidates, let me rephrase, most people are not comfortable looking at themselves talking so this in itself can make them uncomfortable, and irrelevant. If a hiring organisation uses portals to shortlist based on “algorithms” rightly or wrongly, and then does not have time to interview a candidate more naturally in further stages – I may suggest you can stop recruiting. Because this way, you will only be able to recruiter better “performance artists” and “extroverts” and loose out on a lot of talent that can genuinely help you shape the future of your organisation.

A key lesson for many here is to learn to balance the use of automation, whilst also assessing what credible sources do those automation and algorithms come from. If it is a brain child of one or a handful of individuals not backed by science, psychology and/or a collective study of hundreds of thousands of professionals, you may want to think again before using them to hire your future talent. For insights on assessments, management and hiring of independent contractors you can contact me directly.

To read more on similar topics explore our blogs; to speak with us about employer’s hubs and how we can help transform your contractor talent management by bringing efficiencies through our simple cloud platform, get in touch. We are a free platform for interims with thousands of jobs refreshed daily, join us today.

About the Author:

Bhumika Zhaveri’s expertise lies in business strategy, change, human resources and talent management. Her experience is built over years in varied sectors where she has worked within Recruitment, Resourcing and HR. Now as Founder & CEO of InteriMarket a platform for Contract/Interim Talent Management. She is a firm believer of success through people, change and culture!


If you want to share this article the reference to Bhumika Zhaveri and The HR Tech Weekly® is obligatory.

Head of Catering Jobs in NYC

Google for Jobs: Opening the Door for Applicant Experience Chatbots

Google for Jobs: Opening the Door for Applicant Experience Chatbots
Source: TechCrunch

Recently, the Google Cloud Jobs API team unveiled Google for Jobs. By aggregating similar job titles into groups of jobs, job seekers can search and discover relevant jobs in a centralized location, rather than visiting multiple job boards and company career pages. Google says recruiters can expect “more, motivated applicants.”

Google’s entrance to the job search space, brings much needed innovation. In a recent blog post, Google for Jobs: Disrupting the Recruiting Market?, Josh Bersin, details today’s frustrating landscape:

“The bottom line is a lot of headaches and inefficiency in the job market: the average open position receives more than 150 resumes, more than 45% of candidates never hear anything back from the employer, 83% of candidates rate their job search experience poor…”

With Google doing what they do best — organizing information and making it searchable and discoverable, the job search experience will improve. This further catalyzes an already budding, industry-wide movement towards improved candidate engagement.

When coupled with the increasing pervasiveness of “Quick Apply” options, Google’s enhanced job discoverability has officially knocked down all barriers to applying. Recruiters will experience a massive increase in inbound applicants.

As applicant pools grow, recruiters’ needs will shift from, “How do I get applicants to apply to my jobs?” to “How do I engage this new and much larger applicant pool?” The application floodgates have opened and recruiters, already stretched thin, lack the bandwidth to engage.

Here’s where chatbots come in.

Chatbots engage on candidates’ schedules.

Most applicants and recruiters have tight schedules, which makes it hard to find time to connect. With narrow windows of time to communicate, recruiters and applicants often miss each other. Unlike recruiters, chatbots are not limited by time. Rather, they engage with applicants at their convenience.

Chatbots are patient and listen attentively.

In order to move through the ever-growing queue of applicants, recruiters often rush through the most important aspect of their job: building relationships with candidates. Recruiters strive to listen to candidates, to empathize with their situation and to provide thoughtful feedback and context about the job. Unfortunately, buckling under the pressure to quickly engage, screen and assess, recruiters lack the bandwidth to provide such a thoughtful experience. Chatbots, on the other hand, can be patient when recruiters cannot. Chatbots fulfill the outcome recruiters desire, but are too overburdened to achieve themselves.

Chatbots allow recruiters to make data-driven decisions.

Lastly, similar to “Quick Apply” applications, rushed interviews reduce the data available to recruiters. Short, distracted phone screens provide an incomplete picture of a candidate. Not only does this force recruiters to make decisions based on data they know is incomplete, but candidates are left feeling misrepresented. Chatbots patiently listen to applicants in order to gather a complete picture of their experiences and skills as they relate to the role in question — effectively replicating the outcome recruiters seek in the initial phone screen, but with more holistic data.

Candidates deserve a hiring experience that is un-rushed, attentive and personable. Recruiters want this too, but lack the bandwidth to provide such engagement at scale. The introduction of Google for Jobs further compounds this dilemma.

🙋 ️Enter Wendy.

Wendy is an Applicant Experience Chatbot. She automates the experience recruiters wish they could provide for every applicant. She does not seek to replicate the candidate-recruiter relationship itself. Rather, she replicates, at scale, the outcome a conversation between candidate and recruiter achieves. She aims to engage candidates in an attentive, empathetic way that makes them comfortable enough to open up about their professional accomplishments and career goals — just as a recruiter seeks to do.

What other implications do you think Google for Jobs has on the industry? Let us know in the comments or start a conversation with us on Twitter: @wadeandwendy.


If you want to share this article the reference to Wade & Wendy and The HR Tech Weekly® is obligatory.

Statistics

Hiring Statistics You Need to Know for 2017 (Infographic)

Statistics

While we are aware that the job landscape is always changing – with new technology, automation and outsourcing removing jobs, and new startups popping up everywhere you look – it’s sometimes hard to see the big picture. But, as a hiring manager or even business leader, it is important to know where the industry is headed. Background check company, EBI, has put together a list of 60 hiring statistics that are important for every HR professional. Looking at everything from the hiring process to gender and diversity breakdown in the workplace, it paints a telling picture of the issues HR professionals face every day.

You can see the highlights in the infographic below:

Hiring Statistics You Need to Know for 2017 | Infographics by EBI


Source: 60 Hiring Statistics You Need to Know for 2017

Leveraging the Best of AI for Outstanding Hiring Results

Leveraging the Best of AI for Outstanding Hiring Results

Written by Laura Mather, Founder and CEO at Unitive, Inc. (Talent Sonar).

Laura Mather, Founder and CEO at Unitive, Inc. (Talent Sonar)

Every hiring team is asking the same question: is this candidate the right person for the job? This should be a fairly simple question to answer, but after the resume review and the interview are over, it’s become pretty clear that humans don’t always have the best intuition. Although we sometimes do get it right, sometimes just isn’t enough. Bad hires are hugely expensive for any organization of any size. Tony Hsieh, the CEO Zappos has estimated that bad hires cost the company “well over $1 million.” The US Department of Labor has estimated that a bad hire can cost a company at least 30 percent of that employee’s first-year earnings.

While many companies are feeling pressure to scale and expand quickly, no company can afford to absorb these losses, especially when you factor in the time and energy your current employees will expend hiring and training them.

Ineffective hiring techniques hurt your chances of finding great hires in numerous ways. Not only will you miss great applicants, or let qualified candidates get lost in the shuffle, bad hiring techniques can also translate into bad candidate experiences, meaning that you may be losing great candidates to competitors just because your hiring process was tedious or confusing.

LinkedIn Talent Solutions found that a shocking 83 percent of applicants said a negative interview experience changed their opinion about a role or a company they had once thought of positively. Not only can a bad experience influence a candidate but a good experience can have an even stronger reaction: 87 percent of respondents to LinkedIn said that a good interview experience improved their opinion of a company they had previously doubted.

When an unstructured and unreliable hiring process leaves candidates feeling confused, frustrated, or even disappointed, this can damage both our hiring outcomes and your company’s reputation. One study found that 72 percent of candidates who had a poor hiring experience shared that experience publicly on sites like Glassdoor.

So how can you leverage the best in people analytics to create a hiring system that consistently yields great hires while also maintaining a positive candidate experience? The answer lies in the careful calibration of human intuition and machine learning. While our “gut instincts” are often wrong, good HR teams are able to combine those human reactions with great data and software that guide hiring decisions but don’t dictate them.

For companies of any size, in any sector, the key to consistently successful hiring isn’t automation alone: it’s structure throughout the process and alignment at every level of the team from executives to managers and recruiters. Software can help combine these crucial components, ensuring teams are guided by the same principles and priorities so that candidates have uniform, positive experiences. Software can also stitch machine learning and AI tools into every step so they become an intuitive part of the process, instead of a cumbersome addition.

Although AI has mostly been used during resume review, this technology can and should be expanded to rest of the process, guiding how managers draft job descriptions so that they are accurate, communicate the most important aspects of the position, and will appeal to a wide range of candidates, ensuring your applicants represent the full pool of potential talent that can succeed in this role.

AI can also help continually guide HR teams back to the qualities and capacities that matter most to this position. That can mean helping interviewers create questions that are relevant, behavior-based, and consistent with other interviewers so that every candidate has a consistent experience. It can also mean scoring candidates so that HR teams can see, without a doubt, which applicants are qualified and why.

Whether you are a Fortune 100 powerhouse or a nimble and growing startup, whether you are looking for a C-Suite executive or a daring creative, your needs remain the same: find great candidates with proven abilities to succeed and convince them to work for you and not your competitor. While the objectives are clear, the task is herculean. With the structure, support, and guidance of AI hiring technologies, HR professionals are finally fully empowered to create meaningful interviews, build positive relationships with candidates, and make great decisions and find the perfect hire every time.


If you want to share this article the reference to Laura Mather and The HR Tech Weekly® is obligatory.

Recruitment Tools: The Magic Lamp for HR

Recruitment Tools: The Magic Lamp for HR

Written by Sachin Gupta, CEO and Co-Founder, HackerEarth.

Sachin Gupta, CEO and Co-Founder, HackerEarth

Ask any business right now about their top challenges — chances are good that recruiting and retaining talent will be on the top three in the priority list. Smart organizations are aware that they’re only as good as their employees and will prioritize in hiring the best of the best for their organizations.

As technology continues to evolve, it is playing a significant role in the way companies approach the talent search and the hiring process. With companies not really carrying labels that say they are tech or non-tech anymore, finding and retaining great tech talent is what the hiring game is now all about.

According to a recent 2017 survey, finding and hiring top tech talent is what keeps the executives up at night. It has been the management’s greatest concern for the last five years. However, with recruiters latching on to online recruitment tools that are “smartifying” the hiring process, tech hiring was never easier, and never more reliable.

Time for a change

When LinkedIn and other online job applications first began to gain traction, they were considered as supplements to the traditional paper résumé and in-person interview. Today, the world of recruiting has gone nearly 100-percent digital. Traditional recruiting processes often fail to acquire the best and brightest. With smart online assessment tools, recruiters are no longer limited to interviewing candidates within a limited geographical radius, and they are less likely to make bad hires based just on snazzy résumés. They don’t need to put in hours sifting through résumés that are often not a reflection the saleable skills or manually evaluating tests. There is no place for unconscious bias either.

Online recruitment tools are replacing traditional methods that don’t always work. Entrepreneurs are ready to invest big in amazing technical assessment tools that automate complex screening and recruiting tasks to add real value.

Using traditional hiring methods are deal-breakers especially for companies looking at acquiring quality technical talent. There is no one-size-fits-all approach. Different requirements warrant different tools or processes. Be it a campus recruitment drive or hiring for niche profiles, online technical assessment tools have an answer. So, what is the reason for these tools to be highly successful?

Scale

A leading retailer wanted to scale its hiring process across Indian cities. When its current hiring process did not support the rapid expansion, the global e-com leader opted for online technical assessment tool. It allowed them to have multiple administrators and enabled them to conduct multiple recruitment drives from several cities for various roles and functions. The tool allowed them to assess thousands of candidates remotely and the proctoring mechanisms ensured a fair assessment. In a span of six months, the company conducted 200+ hiring drives and assessed over 27,000 candidates in different cities.

Time

Minimizes manual filtering of hundreds of résumés thus saving time. Significantly reduces the number of interviews your technical team needs to take to find the right candidate. Prevents the number of candidates from becoming a bottleneck because any number of candidates can be tested simultaneously. This meant hiring managers and technical managers spending less time assessing candidates and wasting no time on irrelevant candidates.

Efficient campus hiring

Large enterprises usually hire developers in big numbers. Campus hiring is one of the many modes that these organizations use. Using an online recruiting tool, these companies can accurately measure the technical skills of candidates. Online tools will also help these companies to hire from different campuses across states thus achieving the numbers they want to.

Exhaustive Question Library

Some of the best tools nowadays supports multiple question types including programming, MCQ, subjective, android, and front-end programming. These libraries help companies to save time on problem setting and test candidates on assorted topics.

Proctoring measures

Recruiting tools come with the best proctoring measures which helps the recruiters test candidates remotely. These tools have built-in features like plagiarism detector, candidate snapshot, restricting multiple logins among others.

The conclusion

Hiring quality tech talent is the common denominator across all organizations. And the online recruiting tools are significantly better at finding them quality talent than the traditional processes that have been followed till now.

By using a tool such as the automated assessment platforms, even non-tech recruiters can conduct technical screening without a hitch. These coding platforms are significantly better than the processes that already exist in these companies. As these tools are easily integrable with the recruiting workflow of an organization, software giants should be happy to take this route.

To rephrase the famous saying from the movie Ratatouille, “Not everyone can become a great developer; but a great developer can come from anywhere” Make sure you don’t lose out on them.


If you want to share this article the reference to Sachin Gupta and The HR Tech Weekly® is obligatory.

How Machine Learning is Revolutionizing Digital Enterprises

How Machine Learning is Revolutionizing Digital Enterprises

According to the prediction of IDC Futurescapes, two-thirds of Global 2000 Enterprises CEOs will center their corporate strategy on digital transformation. A major part of the strategy should include machine-learning (ML) solutions. The implementation of these solutions could change how these enterprises view customer value and internal operating model today.

If you want to stay ahead of the game, then you cannot afford to wait for that to happen. Your digital business needs to move towards automation now while ML technology is developing rapidly. Machine learning algorithms learn from huge amounts of structured and unstructured data, e.g. text, images, video, voice, body language, and facial expressions. By that it opens a new dimension for machines with limitless applications from healthcare systems to video games and self-driving cars.

In short, ML will connect intelligently people, business and things. It will enable completely new interaction scenarios between customers and companies and eventually allow a true intelligent enterprise. To realize the applications that are possible due to ML fully, we need to build a modern business environment. However, this will only be achieved, if businesses can understand the distinction between Artificial Intelligence (AI) and Machine Learning (ML).

Understanding the Distinction Between ML and AI

Machines that could fully replicate or even surpass all humans’ cognitive functions are still a dream of Science Fiction stories, Machine Learning is the reality behind AI and it is available today. ML mimics how the human cognitive system functions and solves problems based on that functioning. It can analyze data that is beyond human capabilities. The ML data analysis is based on the patterns it can identity in Big Data. It can make UX immersive and efficient while also being able to respond with human-like emotions. By learning from data instead of being programmed explicitly, computers can now deal with challenges previously reserved to the human. They now beat us at games like chess, go and poker; they can recognize images more accurately, transcribe spoken words more precisely, and are capable of translating over a hundred languages.

ML Technology and Applications for Life and Business

In order for us to comprehend the range of applications that will be possible due to ML technology, let us look at some examples available currently:

  • Amazon Echo, Google Home:
  • Digital assistants: Apple’s Siri, SAP’s upcoming Copilot

Both types of devices provide an interactive experience for the users due to Natural Language Processing technology. With ML in the picture, this experience might be taken to new heights, i.e., chatbots. Initially, they will be a part of the apps mentioned above but it is predicted that they could make text and GUI interfaces obsolete!

ML technology does not force the user to learn how it can be operated but adapts itself to the user. It will become much more than give birth to a new interface; it will lead to the formation of enterprise AI.

The limitless ways in which ML can be applied include provision of completely customized healthcare. It will be able to anticipate the customer’s needs due to their shopping history. It can make it possible for the HR to recruit the right candidate for each job without bias and automate payments in the finance sector.

Unprecedented Business Benefits via ML

Business processes will become automated and evolve with the increasing use of ML due to the benefits associated with it. Customers can use the technology to pick the best results and thus, reach decisions faster. As the business environment changes, so will the advanced machines as they constantly update and adapt themselves. ML will also help businesses arrive on innovations and keep growing by providing the right kind of business products/services and basing their decisions on a business model with the best outcome.

ML technology is able to develop insights that are beyond human capabilities based on the patterns it derives from Big Data. As a result, businesses would be able to act at the right time and take advantage of sales opportunities, converting them into closed deals. With the whole operation optimized and automated, the rate at which a business grows will accelerate. Moreover, the business process will achieve more at a lesser cost. ML will lead businesses into environs with minimal human error and stronger cybersecurity.

ML Use Cases

The following three examples show how ML can be applied to an enterprise model that utilizes Natural Language Processing:

  • Support Ticket Classification

Consider the case where tickets from different media channels (email, social websites etc.) needs to be forwarded to the right specialist for the topic. The immense volume of support tickets makes the task lengthy and time consuming. If ML were to be applied to this situation, it could be useful in classifying them into different categories.

API and micro-service integration could mean that the ticket could be automatically categorized. If the number of correctly categorized tickets is high enough, a ML algorithm can route the ticket directly to the next service agent without the need of a support agent.

  •  Recruiting

The job of prioritizing incoming applications for positions with hundreds of applicants can also be slow and time consuming. If automated via ML, the HR can let the machine predict candidate suitability by providing it with a job description and the candidate’s CV. A definite pattern would be visible in the CVs of suitable candidates, such as the right length, experience, absence of typos, etc. Automation of the process will be more likely to provide the right candidate for the job.

  • Marketing 

ML will help build logo and brand recognition for businesses in the following two ways:

  1. With the use of a brand intelligence app, the identification of logos in event sponsorship videos or TV can lead to marketing ROI calculations.
  2. Stay up to date on the customer’s transactions and use that behavior to predict how to maintain customer loyalty and find the best way to retain them.

How Enterprises Can Get Started Implementing Machine Learning

Businesses can step into the new age of ML and begin implementing the technique by letting the machines use Big Data derived from various sources, e.g. images, documents, IoT devices etc to learn. While these machines can automate lengthy and repetitive tasks, they can also be used to predict the outcome for new data. The first step in implementation of ML for a business should be to educate themselves about its nature and the range of its applications. A free openSAP course can help make that possible.

Another step that can bring a business closer to ML implementation is data preparation in complex landscapes. The era of information silos is over and there is an imperative need for businesses to gather data from various sources, such as customers, partners, and suppliers. The algorithms must then be provided open access to that data so they can learn and evolve. The Chief Data Officer of the company can oversee the ML integration process.

To start with completely new use cases for Machine Learning is not easy and requires a good understanding of the subject and having the right level of expertise in the company. A better starting point for many companies would be to rely on ML solutions already integrated into standard software. By that it will connect seamless with the existing business process and immediately start to create value.

Lastly, businesses should start gathering the components necessary for building AI products. Among the requirements would be a cloud platform capable of handling high data volume that is derived from multiple sources. The relevant people are as important to this step as are the technology and processes. After all, they would be the ones who will be testing the latest digital and ML technologies.

If you want more information on SAP Machine Learning, then go here to subscribe to the webinar on Enabling the intelligent Enterprise with Machine Learning.

The presenters include Dr. Markus Noga: VP Machine Learning Innovation Center Network, SAP SE. You can follow him on Twitter. Ronald van Loon is the other presenter for the webinar. Mr. van Loon is counted among the Top 10 Big Data expert and is an IoT Influencer. You can also follow him on Twitter.


Source: How Machine Learning is Revolutionizing Digital Enterprises | Ronald van Loon | Pulse | LinkedIn

Is AI Really A Threat To Jobs?

Artificial Intelligence | The HR Tech Weekly®

Has the future obliteration of jobs by automation been over-exaggerated? At the end of last year Bank of England Governor Mark Carney warned that up to 50% of UK jobs could be wiped out by automation. A recent report suggests that so far the AI-jobs apocalypse has yet to materialise.

Recent research from the Chartered Institute of Ergonomics and Human Factors (CIEHF) together with CV-Library found that two thirds of businesses had not yet witnessed job losses due to automation. Over a third believed that automation had actually increased the number of jobs available.

This is a view broadly supported by Deloitte. In 2015, it highlighted the benefits of automation and its ability to create better quality jobs by removing tedious and dull work which increases the potential for errors due to boredom and distractions. Its research also noted that as a result of automation:

  • 3.5 million low risk jobs have been created since 2001, compared to 800,000 high risk jobs lost.
  • Each new low-risk job pays a salary £10,000 higher than the high risk job it replaced.

This does not alleviate concerns over automation. The CIPD’s Employee Outlook Survey also notes that nearly a quarter of employees are concerned that their job – or parts of it – may be automated within the next five years. Similarly, PwC’s UK Economic Outlook predicts that 30% jobs in the UK are at risk from automation by the early 2030s. Like Deloitte, however, it notes that the nature of available jobs will change. Sectors at highest risk of job losses through automation include transport, manufacturing, and wholesale and retail. Education and health and social work and education are at the lowest risk of being replaced.

Ongoing resistance to AI

The CIEHF/CV Library survey reports a ‘resistance’ among employees to automation as employers are failing to communicate its benefits effectively and HR remains one of the most reluctant to positively embrace automation within talent management strategies. Deloitte’s 2017 Human Capital Trends Survey found that progress towards people analytics in the last year remains stubbornly slow. This is perhaps unsurprising as nearly half of recruitment professionals are still not using applicant tracking software in hiring processes.

HR must first acknowledge the advantages of automation in recruitment to communicate its benefits more effectively. In hiring processes, this means the automation of mundane procedures, including personalised e-mails to job applicants, effective, streamlined screening to reduce unconscious bias and insights into key hiring metrics that impact your ability to hire. It also enables hiring teams to create a more effective onboarding processes to improve retention of new hires.

But why is HR so reluctant to embrace technology?

An article in the Harvard Business Review suggests that the resistance to AI is twofold. To accept and take advantage of automation, consumers must trust both in the technology and in the business delivering the innovation. In recruitment that means HR must have confidence in the supplier of recruitment software and its ability to deliver benefits to its hiring process.

The article also highlights three key points which are essential to gaining that confidence:

Cognitive compatibility : In other words, make it easy to understand. The more complex the nature of the technology, the less likely consumers are to trust its ability achieve desired goals. For HR, that goal is to streamline hiring processes to ensure not only faster hiring but a better quality of hire.

Trialability : A trial of potential new technology helps to understand the benefits and reduce any reluctance to embrace technology.

Usability : To encourage buy-in among tech-resistant hiring teams, technology, especially HR software, must be easy to use.

Recruitment software aside, as companies continue to invest in technology it is vital to maintain employee buy-in and foster trust by investing in upskilling employees to equip them to use digital skills in the workplace. The UK faces a significant digital skills crisis in addition to a wider talent shortage but employers are failing to invest in the necessary training to equip employees with vital skills. Training and development is essential for businesses that wish to not only retain but to continue to attract talent to their brand. It will also go some way to overcoming ‘resistance’ to technology in the workplace.

Ethical concerns

Overcoming ethical concerns is an issue that HR must consider in the future.

The EU[1] has proposed the creation of a European agency to provide technical, ethical and regulatory advice on robotics and AI, including the consideration of a minimum income to compensate people replaced by robots and a ‘kill switch’ for malfunctioning AI systems. A similar concern was recently expressed by the International Bar Association which warned that AI could ultimately lead to the introduction of legislation for quotas of human workers in the future[2].

While the debate over the benefits of AI at work continues, there is no doubt about the struggle that employers face to hire and retain qualified candidates. HR software is HR’s first step towards embracing the benefits of automation and creating more effective talent management strategies.

[1] MEPs vote on robots' legal status - and if a kill switch is required

[2] Rise of robotics will upend laws and lead to human job quotas, study says

A version of this article first appeared on Advorto’s website.

 

Unlocking Business Growth through HR and People Science

Unlocking Business Growth through HR and People Science

Written by Adam Hale, EVP of Sage People.

Why fast-growth companies are bounding ahead?

For businesses to sustain growth, be more productive, and attract and retain the best talent in today’s increasingly global and competitive climate, they need to use data intelligently. Data analytics has been happening for a long time in marketing, sales and finance, but now we’re seeing HR wake up to the benefits. Traditionally, HR functions capture information about employees passively in order to meet legislative requirements but organizations are now realizing it has far more potential with data analytics which is also leading to the rise of the Chief People Officer role.

While 83% of HR leaders recognize that all people decisions should be based on data and analytics, the reality in the workplace is very different. Recent research Fairsail (now Sage People) conducted amongst 500 global HR leaders for its report ‘The use of people science in fast growth companies’ showed that only 37% of those surveyed claiming to already use a data-centric approach.

Why fast-growth companies are bounding ahead

However, there is one business group making the most of its people science capabilities: the fast-growing ‘gazelle’ organizations – companies which have increased their revenues by at least 20% annually for four years or more. The research shows that these organizations are far more advanced in HR than the average company. They have full HR automation (80% v 53%) so they can report faster and more easily on a range of influential HR metrics. If asked to report on headcount within a single day, 84% can do it; that’s 16 percentage points better than non-gazelles. They can more easily report on high potential employees (58% v 42%) and on personal growth (58% v 41%).

These gazelle organizations can see what’s working and what needs to change and can take action confidently to make sure they’re supporting employees to achieve their potential. While gazelles are the one’s bounding ahead, all is not lost as almost every organization we spoke to did have an awareness of the potential to use people and HR data to improve their business.

Use Chief People Officers to close the gap

Even if they haven’t yet marshalled it effectively or decided exactly how they’ll use it, a staggering 92% said they’d like to use people science to improve their business. And another 65% said that in the next 12 months they need to achieve greater data visibility.

The research also positively showed a movement across all organizations to make a highly visible change that reflects the shift to a people focus: 17% have appointed a Chief People Officer to put people science at the heart of their business. The gap between the gazelle approach and the non-gazelle approach looks set to narrow in the very near future, as all businesses take action on their ever-growing awareness of the importance of people analytics.

Tap into data to unlock rapid growth

So what can we learn today from these market-leading organizations? Seeking and seizing opportunities and using every lever a company can get its hands on to improve performance is the key to rapid growth. Organizations shouldn’t be afraid to explore the latest people thinking, or adopt the tools that gather data and turn it into business intelligence. The challenge is to put systems and tools in place to collect and analyze it for tangible benefit – as 31% revealed, they don’t currently have the right technology in place to interpret the necessary people science. Automation helps companies move away from old-style HR with its laborious administration and manual processes and spreadsheets. With this, people teams should be able to explore the workforce data to understand what employees want and need. They can take action to provide great workforce experiences that makes the most of talent to fuel productivity and business growth.

To read the full ‘The use of people science in fast growth companies’ report, please visit www.fairsail.com.

About the Author:

Adam Hale, CEO at Fairsail

Adam Hale, EVP of Sage People, previously acted as Executive Chairman and Non Executive Director having spent over 30 years in the technology industry. He was formerly Head of Software and European Technology at Russell Reynolds Associates, the leading executive search firm and before that ran large system implementation projects at Accenture. Adam is also a committee member of the Technology Leadership Group (TLG) for the Prince’s Trust.


If you want to share this article the reference to Adam Hale and The HR Tech Weekly® is obligatory.

3 Ways HR Will Evolve in the Future

3 Ways HR Will Evolve in the Future

Believe it or not, automation is changing our entire lives, the way we live, think and work. As quoted by Mr. Abhijit Bhaduri, author of Digital Tsunami, “Humans resist change, machines don’t.” We are at a age where we no longer can nor should resist change. That said, technology is also massively impacting the HR functions. Most of the traditional support functions of HR, such as payroll, attendance etc. are being automated. Adding to the progression, chatbots are further driving more engagement with its personalized attributes, and is further adding up to redefining the HR role.

Ripples in the Water

One might wonder, will the rapid pace of digitization re-define HR? Of course yes, with millennials making up more than half of the current workforce — and predicted to make up 75 percent by 2020 — HR has to embrace technologies to keep at par with employee and business demands.

The Effect of Big Data

A lot of work in HR used to be related to adherence to compliances and therefore, huge amount of work related to paperworks was involved. But, now things have changed. Online portals and platforms provide HR with all the information that they need. Today’s technology gives HR professionals access to the power of Big Data and changes the way businesses understand their customers, build their own brands and communicate to prospective employees.

One of the boons of Big Data is Predictive Analytics. In big corporations, it is very difficult to keep a track of each employee. Predictive analytics enables HR to understand which employee needs an additional training.

High Up in the Clouds

Another technology which is impacting HR in a big way. Gathering and storing of information has always been a major function of the HR department, and the stack of files not only waste office space but are very difficult to trace as well. Can you even imagine, a millennial, who is always glued to his smartphone will have the patience to go through all the piles of paper?

High Up in the Clouds

Thanks to cloud technology, all of this information can instead be stored in the cloud. No longer does an employee need to tick the boxes while filling up a feedback form which again runs the risk of getting lost. All the employee information like tax documents, payroll, feedback etc can be stored online securely.

Cloud-based systems and Big Data go hand in hand. With Machine Learning emerging steadily, all these data will make a lot of sense few years down the line, it all depends how well can one derive relevant information out of it.

Chat with the Bots

There are some information which are very subjective in nature, like how to fill the Form 19 or file for the income tax returns. It makes no sense if the employee walks up to the HR managers for day-to-day queries or any concerns they might have regarding their pay, leaves, performance etc. To narrow down the gap of communication between the employees and the HR, PeopleStrong recently launched India’s first HR chatbot ‘Jinie’. From a transactional interface with employees to a conversational interface, Jinie the India’s first HR Chatbot will be able to provide the next level of experience to its employees.

In the era of smartphones, this will be a great boost in employee engagement.

These are few of the many ways in which the HR domain will change and adapt itself to digitization. With the burden of a lot of paperwork gone from the shoulders and with new data in hand, HR department will be fully equipped to make the employees life much easier and will add more value in business.


If you want to share this article the reference to Bangabdi Roy Chowdhury and The HR Tech Weekly® is obligatory.